code: def run_cdc_pipeline():
      cdc_settings = create_example_settings()
      event_clusters, entity_clusters = run_example(cdc_settings)
  
      print("-=Cross Document Coref Results=-")
      print_results(event_clusters, "Event")
      print("################################")
      print_results(entity_clusters, "Entity")
  
file_path: nlp-architect/examples/cross_doc_coref/cross_doc_coref_sieves.py
imports: import logging
  from typing import List
  from nlp_architect import LIBRARY_ROOT
  from nlp_architect.common.cdc.cluster import Clusters
  from nlp_architect.common.cdc.topics import Topics
  from nlp_architect.data.cdc_resources.relations.referent_dict_relation_extraction import ReferentDictRelationExtraction
  from nlp_architect.data.cdc_resources.relations.relation_types_enums import RelationType
  from nlp_architect.data.cdc_resources.relations.wikipedia_relation_extraction import WikipediaRelationExtraction
  from nlp_architect.data.cdc_resources.relations.word_embedding_relation_extraction import WordEmbeddingRelationExtraction
  from nlp_architect.models.cross_doc_coref.sieves_config import EventSievesConfiguration, EntitySievesConfiguration
  from nlp_architect.models.cross_doc_coref.sieves_resource import SievesResources
  from nlp_architect.models.cross_doc_coref.system.sieves_container_init import SievesContainerInitialization
  from nlp_architect.models.cross_doc_sieves import run_event_coref, run_entity_coref
label_desc: Use image node_id 5 for calling a global function with example usage: run_cdc_pipeline() without return types